DataSheet2_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF حسب András Micsonai (801004)

"…Here, we propose an automatized binary disorder–order classification method by analyzing far-UV CD spectroscopy data. …"

DataSheet3_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.xlsx حسب András Micsonai (801004)

"…Here, we propose an automatized binary disorder–order classification method by analyzing far-UV CD spectroscopy data. …"

DataSheet1_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF حسب András Micsonai (801004)

"…Here, we propose an automatized binary disorder–order classification method by analyzing far-UV CD spectroscopy data. …"

Summary of the AdaBoost classification for the two exercises SDT and SLST. حسب Jindřich Adolf (17334216)

Recognition of each neuron’s digital identity. حسب Yuxiang Wu (748543)

a-g SHapley Additive exPlanation (SHAP) values for model features by class (MIS-C/Non-MIS-C PASC). حسب Vitaly Lorman (16814000)

Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf حسب Konrad Stawiski (4753380)

"…We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset.…"

DataSheet_2_MRI-Based Radiomics to Differentiate between Benign and Malignant Parotid Tumors With External Validation.pdf حسب Francesca Piludu (10706391)

"…The model with the final feature set was achieved using the support vector machine binary classification algorithm.</p>Results<p>Models for discriminating between Warthin’s and malignant tumors, benign and Warthin’s tumors and benign and malignant tumors had an accuracy of 86.7%, 91.9% and 80.4%, respectively. …"

DataSheet_1_MRI-Based Radiomics to Differentiate between Benign and Malignant Parotid Tumors With External Validation.xlsx حسب Francesca Piludu (10706391)

"…The model with the final feature set was achieved using the support vector machine binary classification algorithm.</p>Results<p>Models for discriminating between Warthin’s and malignant tumors, benign and Warthin’s tumors and benign and malignant tumors had an accuracy of 86.7%, 91.9% and 80.4%, respectively. …"

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

"…The accuracy obtained by the proposed method was reported for binary classification. More importantly, the classification results of the less commonly reported MCIs vs. …"

Data_Sheet_3_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.xlsx حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"

Image_1_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.JPEG حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"

Image_2_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.JPEG حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"

Data_Sheet_2_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.xlsx حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"

Data_Sheet_1_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.xlsx حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"

Data_Sheet_4_Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.pdf حسب Kirsty E. Waddington (5754545)

"…We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.…"